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The phonon-related properties of crystalline polymers are highly relevant for various applications. Their simulation is, however, particularly challenging, as the systems that need to be modeled are often too extended to be treated by ab initio methods, while classical force fields are too inaccurate. Machine-learned potentials parametrized against material-specific ab initio data hold the promise of being extremely accurate and also highly efficient. Still, for their successful application, protocols for their parametrization need to be established to ensure an optimal performance, and the resulting potentials need to be thoroughly benchmarked. These tasks are tackled in the current manuscript, where we devise a protocol for parametrizing moment tensor potentials (MTPs) to describe the structural properties, phonon band structures, elastic constants, and forces in molecular dynamics simulations for three prototypical crystalline polymers: polyethylene (PE), polythiophene (PT), and poly-3-hexylthiophene (P3HT). For PE, the thermal conductivity and thermal expansion are also simulated and compared to experiments. A central element of the approach is to choose training data in view of the considered use case of the MTPs. This not only yields a massive speedup for complex calculations while essentially maintaining DFT accuracy, but also enables the reliable simulation of properties that, so far, have been entirely out of reach. [ABSTRACT FROM AUTHOR]

The presence of antibiotics in soils is increasing drastically in last decades due to the intensive farming industry and excessive human consumption. Clay minerals are one of the soil components with great adsorption capacity for organic pollutants. The study of interactions between antibiotics and mineral surfaces will give us scientific knowledge of these pollutants through soils. In this work, we study the adsorption of the antibiotic ciprofloxacin in the clay mineral fraction of soils from the Argentinian zone of Santa Rosa (Corrientes), in a collaborative research of experiments and atomistic modelling calculations of the intercalation of ciprofloxacin in the interlayer space of montmorillonite. Adsorption and desorption isotherms were performed and compared with different isotherm models. Additionally, enthalpy, entropy, and free energy were determined from equilibrium constants at a function of temperature. All these experiments and calculations lead to the conclusions that two adsorption types of ciprofloxacin are found on clay minerals: one weakly sorbed that is released during the desorption experiments, and other one strongly joined that remains in the soil. [ABSTRACT FROM AUTHOR]

Machine learning potentials, particularly the deep potential (DP) model, have revolutionized molecular dynamics (MD) simulations, striking a balance between accuracy and computational efficiency. To facilitate the DP model's integration with the popular MD engine OpenMM, we have developed a versatile OpenMM plugin. This plugin supports a range of applications, from conventional MD simulations to alchemical free energy calculations and hybrid DP/MM simulations. Our extensive validation tests encompassed energy conservation in microcanonical ensemble simulations, fidelity in canonical ensemble generation, and the evaluation of the structural, transport, and thermodynamic properties of bulk water. The introduction of this plugin is expected to significantly expand the application scope of DP models within the MD simulation community, representing a major advancement in the field. [ABSTRACT FROM AUTHOR]

Context: Ryanodine receptors (RyRs) are large intracellular ligand-gated calcium release ion channels. Mutations in human RyR1 in combination with a volatile anesthetic or muscle relaxant are known to cause leaky RyRs resulting in malignant hyperthermia (MH). This has long been primarily treated with the RyR inhibitory drug dantrolene. Alternatives to dantrolene as a RyR inhibitor may be found through computer-aided drug design. Additionally, molecular dynamics (MD) studies of dantrolene interacting with RyRs may reveal its full mechanism of action. The availability of accurate force field parameters is important for the success of both. Methods: In this study, force field parameters for dantrolene were obtained from the CHARMM General Force Field (CGenFF) program and optimized using the force field toolkit (FFTK) and FFParam programs. The obtained parameters were then validated by a comparison between calculated and experimental IR spectra and normal mode analysis, among other techniques. [ABSTRACT FROM AUTHOR]

Based on the TraPPE force field, previously unknown values of the parameters of the intermolecular interaction potential of trans-decalin were determined. Parametrization was carried out using experimental data on saturated vapor pressure and density at atmospheric pressure. The found parameters make it possible to adequately describe the boiling and condensation lines of trans-decalin and also predict the critical values of pressure, density, and temperature with satisfactory accuracy. Calculations of vapor-liquid phase equilibrium conditions for a binary CO2—trans-decalin mixture in supercritical conditions for CO2 were carried out. When quantitatively comparing the calculated values with experimental data, an underestimation of pressure at a temperature of 345.4 K by 30% is observed, which decreases to 5% for temperatures up to 525 K. [ABSTRACT FROM AUTHOR]

This paper presents a United Atom (UA) force field for simulating hydrocarbon molecules in bituminous materials, integrating explicit hydrogens into beads with their parent atom. This method simplifies all-atom molecular models, significantly accelerating Molecular Dynamics (MD) simulations of bitumen by 10 to 100 times. Key advantages include halving the particle count, eliminating complex hydrogen interactions, and decreasing the degrees of freedom of the molecules. Developed by mapping forces from an all-atom model to the centers of mass of UA model beads, the force field ensures accurate replication of energies, forces, and molecular conformations, mirroring properties like pressure and density. It features 17 bead types and 287 interaction types, encompassing various hydrocarbon molecules. The UA force field's stability, surpassing all-atom models, is a notable achievement. This stability, stemming from smoother potential energy surfaces, leads to consistent property measurements and improved stress tensor accuracy. It enables the extension of MD simulations to larger spatiotemporal scales, crucial for understanding complex phenomena such as phase separation in bituminous materials. This foundational work sets the stage for future developments, including refining parameters and introducing new bead types, to enhance the modeling capabilities of the force field, thereby advancing the application and understanding of bituminous materials.

In the last few decades, deep learning (DL) has afforded solutions to macroscopic problems in petroleum engineering, but mechanistic problems at the microscale have not benefited from it. Mechanism studies have been the strong demands for the emerging projects, such as the gas storage and hydrate production, and for some problems encountered in the storage process, which are common found as the chemical interaction between injected gas and mineral, and the formation of hydrate. Emerging advances in DL technology enable solving molecular dynamics (MD) with quantum accuracy. The conventional quantum chemical method is computational expensive, whereas the classical MD method cannot guarantee high accuracy because of its empirical force field parameters. With the help of the DL force field, precision at the quantum chemistry level can be achieved in MD. Moreover, the DL force field promotes the computational speed compared with first-principles calculations. In this review, the basic knowledge of the molecular force field and deep neural network (DNN) is first introduced. Then, three representative open-source packages relevant to the DL force field are introduced. As the most common components in the development of oil and gas reservoirs, water and methane are studied from the aspects of computational efficiency and chemical reaction respectively, providing the foundation of oil and gas researches. However, in the oil and gas problems, the complex molecular topo structures and various element types set a high challenge for the DL techniques in MD. Regarding the computational efficiency, it needs improvement via GPU and parallel accelerations to compete with classical MD. Even with such difficulties, the booming of this technique in the area of petroleum engineering can be predictable.

The presence of antibiotics in soils is increasing drastically in last decades due to the intensive farming industry and excessive human consumption. Clay minerals are one of the soil components with great adsorption capacity for organic pollutants. The study of interactions between antibiotics and mineral surfaces will give us scientific knowledge of these pollutants through soils. In this work, we study the adsorption of the antibiotic ciprofloxacin in the clay mineral fraction of soils from the Argentinian zone of Santa Rosa (Corrientes), in a collaborative research of experiments and atomistic modelling calculations of the intercalation of ciprofloxacin in the interlayer space of montmorillonite. Adsorption and desorption isotherms were performed and compared with different isotherm models. Additionally, enthalpy, entropy, and free energy were determined from equilibrium constants at a function of temperature. All these experiments and calculations lead to the conclusions that two adsorption types of ciprofloxacin are found on clay minerals: one weakly sorbed that is released during the desorption experiments, and other one strongly joined that remains in the soil.

With the advent of the resolution revolution in cryoelectron microscopy (cryo-EM), low-resolution refinement is common, and likewise increases the need for a reliable force field. Here, we report on the incorporation of the OPLS3e force field with the VSGB2.1 solvation model in the structure determination package Phenix. Our results show significantly improved structure quality and reduced ligand strain at lower resolution for X-ray refinement. For refinement of cryo-EM-based structures, we find comparable quality structures, goodness-of-fit, and reduced ligand strain. We also show how structure quality and ligand strain are related to the map-model cross-correlation as a function of data weight, and how that can detect overfitting. Signs of overfitting are found in over half of our cryo-EM dataset, which can be remedied by a re-refinement at a lower data weight. Finally, a start-to-end script for refining structures with Phenix/OPLS3e is available in the Schrödinger 2020-3 distribution.

Intrinsically disordered proteins (IDPs) are widely distributed across eukaryotic cells, playing important roles in molecular recognition, molecular assembly, post-translational modification, and other biological processes. IDPs are also associated with many diseases such as cancers, cardiovascular diseases, and neurodegenerative diseases. Due to their structural flexibility, conventional experimental methods cannot reliably capture their heterogeneous structures. Molecular dynamics simulation becomes an important complementary tool to quantify IDP structures. This review covers recent force field strategies proposed for more accurate molecular dynamics simulations of IDPs. The strategies include adjusting dihedral parameters, adding grid-based energy correction map (CMAP) parameters, refining protein-water interactions, and others. Different force fields were found to perform well on specific observables of specific IDPs but also are limited in reproducing all available experimental observables consistently for all tested IDPs. We conclude the review with perspective areas for improvements for future force fields for IDPs.

Abstract Molecular representation learning is a crucial task to accelerate drug discovery and materials design. Graph neural networks (GNNs) have emerged as a promising approach to tackle this task. However, most of them do not fully consider the intramolecular interactions, i.e. bond stretching, angle bending, torsion, and nonbonded interactions, which are critical for determining molecular property. Recently, a growing number of 3D-aware GNNs have been proposed to cope with the issue, while these models usually need large datasets and accurate spatial information. In this work, we aim to design a GNN which is less dependent on the quantity and quality of datasets. To this end, we propose a force field-inspired neural network (FFiNet), which can include all the interactions by incorporating the functional form of the potential energy of molecules. Experiments show that FFiNet achieves state-of-the-art performance on various molecular property datasets including both small molecules and large protein–ligand complexes, even on those datasets which are relatively small and without accurate spatial information. Moreover, the visualization for FFiNet indicates that it automatically learns the relationship between property and structure, which can promote an in-depth understanding of molecular structure.

Machine learning potentials, particularly the deep potential (DP) model, have revolutionized molecular dynamics (MD) simulations, striking a balance between accuracy and computational efficiency. To facilitate the DP model’s integration with the popular MD engine OpenMM, we have developed a versatile OpenMM plugin. This plugin supports a range of applications, from conventional MD simulations to alchemical free energy calculations and hybrid DP/MM simulations. Our extensive validation tests encompassed energy conservation in microcanonical ensemble simulations, fidelity in canonical ensemble generation, and the evaluation of the structural, transport, and thermodynamic properties of bulk water. The introduction of this plugin is expected to significantly expand the application scope of DP models within the MD simulation community, representing a major advancement in the field.

Low-intensity pulsed ultrasound (LIPUS) is commonly used for bone fracture healing to mechanically stimulate a fracture site and accelerate the repair process. Recent studies reported that LIPUS stimulation could have various effectiveness such as not only fracture healing but also regenerative medicine of articular cartilage and cognitive dysfunction improvement. However, conventional LIPUS devices stimulate both affected and unaffected sites. To promote healing effects at an affected site and enhance therapeutic applications, LIPUS devices should employ acoustic holography, which can control force fields and provide the desired ones to an affected site. However, conventional control algorisms cannot form desired force fields and have not been used in vivo for therapy. In this study, we experimentally investigate the feasibility to control force fields by acoustic holography using an ultrasound transducer array under water for therapy. First, we designed and prototyped a simple device for generating force fields using a 4×4 ultrasound transducer array under water for therapy. Then, we introduced a force field control algorithm developed in our previous study into the prototype force field generator to experimentally verify the controllability to achieve desired force fields for therapy. The findings show that the prototype force field generator meets acoustic intensity enough for fracture healing by focused ultrasound and that the developed control algorism applied to the prototype force field generator forms a two-dimensional force field similar to a rectangular shape assuming a fracture line as a target area and suppresses the acoustic intensity outside the target area.

Thermal conductivities of polybutadiene crosslinked with sulfur as a function of the heat flux autocorrelation function by using an equilibrium molecular dynamic (EMD) simulation were investigated. The Green–Kubo method was used to calculate thermal conductivities. All simulations were performed by applying the LAMMPS software (version 3 Mar 2020) package. The united-atom force field (OPLS-UA) from the Moltemplate software (version 2.20.3) was applied in the simulations. The influence of uniform and random distributions of sulfur in polybutadiene on the final value of thermal conductivities was studied by polymeric model structures with similar and variable degrees of crosslinking. The results showed that for identical degrees of crosslinking, the distribution of crosslinkers in the polymeric model structures significantly influenced the final value of thermal conductivity. Moreover, the influence of the crosslinking degree on the final value of thermal conductivity was studied by considering polymeric model structures with different degrees of crosslinking. The results demonstrate that by having a random distribution of sulfur, the thermal conductivity will be enhanced. However, by increasing the degree of crosslinking to the higher percentage in random crosslinked model structures, the value of thermal conductivity drops significantly due to possible higher crystallization of the model structures, which decrease the degree of freedom for phonon contributions. [ABSTRACT FROM AUTHOR]

This research focuses on obtaining the behavior of chemical compounds with respect to their molecular weight and optimization energy based on the variation in properties in organic carbon links. Here, behavioral analysis of compounds is used in the application of a metal organic framework to denote the high-grade compounds. The grade was selected based on the essential measure of optimization energy and molecular weight, and in turn, depicts the stability of material. Computation of the optimization energy and molecular weight of chemical compounds was performed with Avogadro software. Several force fields can be considered to compute optimized energy. Exclusively, three force fields, namely, the Universal Force Field (UFF), the General Amber Force Field (GAFF), and the Ghemical force field (Ghemical) were selected from Avogadro as these were more relevant to compounds considered in this research. The various chemical compounds examined in this work are Aluminum (Al), Boron (Br), Calcium (Ca), Chlorine (Cl), Indium (In), Potassium (K), Scandium (Sc), Silicon (Si), and Tungsten (W). Hence, molecular modeling of different compounds incorporated with three different force fields was evaluated in this work. In this study, we found that the In structure has more energy reduction, of 22.673 kJ mol−1 in UFF, when compared with the other two force fields. Thus, In has higher potential with more stability. [ABSTRACT FROM AUTHOR]

The applicability of the three steps systematic parametrization procedure (3SSPP) to develop a force field for primary amines was evaluated in the present work. Previous simulations of primary amines show that current force fields (FF) can underestimate some experimental values under room conditions. Therefore, we propose a new set of parameters, for an united atom (UA) model, that can be used for short and long amines which predict correctly thermodynamic and dynamical properties. Following the 3SSPP methodology, the partial charges are chosen to match the experimental dielectric constant whereas the Lennard-Jones (LJ) parameters, 𝜖 and 𝜎, are fitted to reproduce the surface tension at the vapor-liquid interface and the liquid density, respectively. Simulations were initially conducted for the propylamine molecule by introducing three different types of carbon atoms, C𝛼 and C𝛽, with electric charges, and C𝑛, without charge. Then, modifying the charges of the carbons and using the transferable LJ parameters, the new set of constants for long amines were found. The results show good agreement for the experimental dielectric constant and mass density with a percentage error less than 1%, whereas for the surface tension the error is up to 4%. For the short amines, methylamine and ethylamine, the new charges were obtained from a fitting function calculated from the long amines results. For these molecules, the values of the dielectric constant and the surface tension present errors of the order of 10% with the experimental data. Miscibility of the amines was also tested with the new parameters and the results show reasonable agreement with experiments. [ABSTRACT FROM AUTHOR]

Background: Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction. The quality of these studies relies on the quality of the force fields used to represent the systems. Methods: Focusing on small molecules of fewer than 50 heavy atoms, our aim in this work is to compare nine force fields: GAFF, GAFF2, MMFF94, MMFF94S, OPLS3e, SMIRNOFF99Frosst, and the Open Force Field Parsley, versions 1.0, 1.1, and 1.2. On a dataset comprising 22,675 molecular structures of 3,271 molecules, we analyzed force field-optimized geometries and conformer energies compared to reference quantum mechanical (QM) data. Results: We show that while OPLS3e performs best, the latest Open Force Field Parsley release is approaching a comparable level of accuracy in reproducing QM geometries and energetics for this set of molecules. Meanwhile, the performance of established force fields such as MMFF94S and GAFF2 is generally somewhat worse. We also find that the series of recent Open Force Field versions provide significant increases in accuracy. Conclusions: This study provides an extensive test of the performance of different molecular mechanics force fields on a diverse molecule set, and highlights two (OPLS3e and OpenFF 1.2) that perform better than the others tested on the present comparison. Our molecule set and results are available for other researchers to use in testing.

This paper reviews molecular dynamics (MD) concepts on heat transfer analysis of supercritical CO2, and highlights the major parameters that can affect the accuracy of respective thermal coefficients. Subsequently, the prime aspects of construction, transfer identification, and thermal performance are organized according to their challenges and prospective solutions associated with the mutability of supercritical CO2 properties. Likewise, the characteristics of bound force field schemes and thermal relaxation approaches are discussed on a case-by-case basis. Both convective and diffusive states of trans- and supercritical CO2 are debated, given their magnitude effects on molecular interactions. Following the scarcity of literature on similar enquiries, this paper recommended a future series of studies on molecular dynamics models in a large region of supercriticality and phase-interactions for coupled heat and mass transfer systems. This review recognizes that the foremost undertaking is to ascertain the thermo-hydraulic identity of supercritical CO2 for process feasibility of developed technology. [ABSTRACT FROM AUTHOR]

Boron containing compounds (BCCs) aroused increasing interest in the scientific community due to their wide application as drugs in various fields. In order to design new compounds hopefully endowed with pharmacological activity and also investigate their conformational behavior, the support of computational studies is crucial. Nevertheless, the suitable molecular mechanics parameterization and the force fields needed to perform these simulations are not completely available for this class of molecules. In this paper, Amber force field parameters for phenyl-, benzyl-, benzylamino-, and methylamino-boronates, a group of boron-containing compounds involved in different branches of the medicinal chemistry, were created. The robustness of the obtained data was confirmed through molecular dynamics simulations on ligand/β-lactamases covalent complexes. The ligand torsional angles, populated over the trajectory frames, were confirmed by values found in the ligand geometries, located through optimizations at the DFT/B3LYP/6-31g(d) level, using water as a solvent. In summary, this study successfully provided a library of parameters, opening the possibility to perform molecular dynamics simulations of this class of boron-containing compounds. [ABSTRACT FROM AUTHOR]

Host–guest binding, despite the relatively simple structural and chemical features of individual components, still poses a challenge in computational modelling. The extreme underperformance of standard end-point methods in host–guest binding makes them practically useless. In the current work, we explore a potentially promising modification of the three-trajectory realization. The alteration couples the binding-induced structural reorganization into free energy estimation and suffers from dramatic fluctuations in internal energies in protein–ligand situations. Fortunately, the relatively small size of host–guest systems minimizes the magnitude of internal fluctuations and makes the three-trajectory realization practically suitable. Due to the incorporation of intra-molecular interactions in free energy estimation, a strong dependence on the force field parameters could be incurred. Thus, a term-specific investigation of transferable GAFF derivatives is presented, and noticeable differences in many aspects are identified between commonly applied GAFF and GAFF2. These force-field differences lead to different dynamic behaviors of the macrocyclic host, which ultimately would influence the end-point sampling and binding thermodynamics. Therefore, the three-trajectory end-point free energy calculations are performed with both GAFF versions. Additionally, due to the noticeable differences between host dynamics under GAFF and GAFF2, we add additional benchmarks of the single-trajectory end-point calculations. When only the ranks of binding affinities are pursued, the three-trajectory realization performs very well, comparable to and even better than the regressed PBSA_E scoring function and the dielectric constant-variable regime. With the GAFF parameter set, the TIP3P water in explicit solvent sampling and either PB or GB implicit solvent model in free energy estimation, the predictive power of the three-trajectory realization in ranking calculations surpasses all existing end-point methods on this dataset. We further combine the three-trajectory realization with another promising modified end-point regime of varying the interior dielectric constant. The combined regime does not incur sizable improvements for ranks and deviations from experiment exhibit non-monotonic variations. [ABSTRACT FROM AUTHOR]

Molecular representation learning is a crucial task to accelerate drug discovery and materials design. Graph neural networks (GNNs) have emerged as a promising approach to tackle this task. However, most of them do not fully consider the intramolecular interactions, i.e. bond stretching, angle bending, torsion, and nonbonded interactions, which are critical for determining molecular property. Recently, a growing number of 3D-aware GNNs have been proposed to cope with the issue, while these models usually need large datasets and accurate spatial information. In this work, we aim to design a GNN which is less dependent on the quantity and quality of datasets. To this end, we propose a force field-inspired neural network (FFiNet), which can include all the interactions by incorporating the functional form of the potential energy of molecules. Experiments show that FFiNet achieves state-of-the-art performance on various molecular property datasets including both small molecules and large protein–ligand complexes, even on those datasets which are relatively small and without accurate spatial information. Moreover, the visualization for FFiNet indicates that it automatically learns the relationship between property and structure, which can promote an in-depth understanding of molecular structure. [ABSTRACT FROM AUTHOR]

Hydration free energies of small molecules are commonly used as benchmarks for solvation models. However, errors in predicting hydration free energies are partially due to the force fields used and not just the solvation model. To address this, we have used the 3D reference interaction site model (3D-RISM) of molecular solvation and existing benchmark explicit solvent calculations with a simple element count correction (ECC) to identify problems with the non-bond parameters in the general AMBER force field (GAFF). 3D-RISM was used to calculate hydration free energies of all 642 molecules in the FreeSolv database, and a partial molar volume correction (PMVC), ECC, and their combination (PMVECC) were applied to the results. The PMVECC produced a mean unsigned error of 1.01 ± 0.04 kcal / mol and root mean squared error of 1.44 ± 0.07 kcal / mol , better than the benchmark explicit solvent calculations from FreeSolv, and required less than 15 s of computing time per molecule on a single CPU core. Importantly, parameters for PMVECC showed systematic errors for molecules containing Cl, Br, I, and P. Applying ECC to the explicit solvent hydration free energies found the same systematic errors. The results strongly suggest that some small adjustments to the Lennard–Jones parameters for GAFF will lead to improved hydration free energy calculations for all solvent models. [ABSTRACT FROM AUTHOR]

Charge scaling as an effective solution to the experiment–computation disagreement in molecular modelling of ionic liquids (ILs) could bring the computational results close to the experimental reference for various thermodynamic properties. According to the large-scale benchmark calculations of mass density, solvation, and water-ILs transfer-free energies in our series of papers, the charge-scaling factor of 0.8 serves as a near-optimal option generally applicable to most ILs, although a system-dependent parameter adjustment could be attempted for further improved performance. However, there are situations in which such a charge-scaling treatment would fail. Namely, charge scaling cannot really affect the simulation outcome, or minimally perturbs the results that are still far from the experimental value. In such situations, the vdW radius as an additional adjustable parameter is commonly tuned to minimize the experiment–calculation deviation. In the current work, considering two ILs from the quinuclidinium family, we investigate the impacts of this vdW-scaling treatment on the mass density and the solvation/partition thermodynamics in a fashion similar to our previous charge-scaling works, i.e., scanning the vdW-scaling factor and computing physical properties under these parameter sets. It is observed that the mass density exhibits a linear response to the vdW-scaling factor with slopes close to −1.8 g/mL. By further investigating a set of physiochemically relevant temperatures between 288 K and 348 K, we confirm the robustness of the vdW-scaling treatment in the estimation of bulk properties. The best vdW-scaling parameter for mass density would worsen the computation of solvation/partition thermodynamics, and a marginal decrease in the vdW-scaling factor is considered as an intermediate option balancing the reproductions of bulk properties and solvation thermodynamics. These observations could be understood in a way similar to the charge-scaling situation. i.e., overfitting some properties (e.g., mass density) would degrade the accuracy of the other properties (e.g., solvation free energies). Following this principle, the general guideline for applying this vdW-tuning protocol is by using values between the density-derived choice and the solvation/partition-derived solution. The charge and current vdW scaling treatments cover commonly encountered ILs, completing the protocol for accurate modelling of ILs with fixed-charge force fields. [ABSTRACT FROM AUTHOR]

Molecular dynamic (MD) simulations offer a way to study biomolecular interactions and their dynamics at the atomistic level. There are only a few studies of RNA-protein complexes in MD simulations, and here we wanted to study how force fields differ when simulating RNA-protein complexes: 1) argonaute 2 with bound guide RNA and a target RNA, 2) CasPhi-2 bound to CRISPR RNA and 3) Retinoic acid-inducible gene I C268F variant in complex with double-stranded RNA. We tested three non-polarizable force fields: Amber protein force fields ff14SB and ff19SB with RNA force field OL3, and the all-atom OPLS4 force field. Due to the highly charged and polar nature of RNA, we also tested the polarizable AMOEBA force field and the ff19SB and OL3 force fields with a polarizable water model O3P. Our results show that the non-polarizable force fields lead to compact and stable complexes. The polarizability in the force field or in the water model allows significantly more movement from the complex, but in some cases, this results in the disintegration of the complex structure, especially if the protein contains longer loop regions. Thus, one should be cautious when running long-scale simulations with polarizability. As a conclusion, all the tested force fields can be used to simulate RNA-protein complexes and the choice of the optimal force field depends on the studied system and research question.

Based on the TraPPE force field, previously unknown values of the parameters of the intermolecular interaction potential of trans-decalin were determined. Parametrization was carried out using experimental data on saturated vapor pressure and density at atmospheric pressure. The found parameters make it possible to adequately describe the boiling and condensation lines of trans-decalin and also predict the critical values of pressure, density, and temperature with satisfactory accuracy. Calculations of vapor-liquid phase equilibrium conditions for a binary CO2—trans-decalin mixture in supercritical conditions for CO2 were carried out. When quantitatively comparing the calculated values with experimental data, an underestimation of pressure at a temperature of 345.4 K by 30% is observed, which decreases to 5% for temperatures up to 525 K.

"Plant-type" ferredoxins (Fds) in the thylakoid membranes of plants, algae, and cyanobacteria possess a single [2Fe-2S] cluster in active sites and mediate light-induced electron transfer from Photosystem I reaction centers to various Fd-dependent enzymes. Structural knowledge of plant-type Fds is relatively limited to static structures, and the detailed behavior of oxidized and reduced Fds has not been fully elucidated. It is important that the investigations of the effects of active-center reduction on the structures and dynamics for elucidating electron-transfer mechanisms. In this study, model systems of oxidized and reduced Fds were constructed from the high-resolution crystal structure of Chlamydomonas reinhardtii Fd1, and three 200 ns molecular dynamics simulations were performed for each system. The force field parameters of the oxidized and reduced active centers were independently obtained using quantum chemical calculations. There were no substantial differences in the global conformations of the oxidized and reduced forms. In contrast, active-center reduction affected the hydrogen-bond network and compactness of the surrounding residues, leading to the increased flexibility of the side chain of Phe61, which is essential for the interaction between Fd and the target protein. These computational results will provide insight into the electron-transfer mechanisms in the Fds. [ABSTRACT FROM AUTHOR]

The euhedral shapes of pyrite FeS2 are usually exposing three main surfaces: striated (001), smooth (111), and striated (210), leading to the cubical, octahedral, and pyritohedral morphology, respectively. The macroscopic striations, sometimes called triglyphs on cubic crystals, are parallel on specific surfaces and aligned to the <100> directions. Other types of striated and unstriated (hkl) surfaces can be observed on pyrite crystals from Peru, a country offering a rich diversity of pyrite shapes. A rare specimen from Elba Island (Italy) is a pyritohedron with uncommon directions of striations (so-called "negative" striations, first described in Japanese minerals). The Wulf kinetic growth and the periodic bond chain (PBC) theories were not relevant enough to explain crystal shapes, the texture of the surfaces, and twinning. To bring some new insights on crystal growth, twinning, and anisotropy, pyrite samples are analyzed using XRD, SEM, and EDS techniques coupled with atomistic simulations. A first analysis points out that sulfur terminations play a key role in the growth of striations in distinguishing the six <001> directions. The negative striated pyritohedral pyrite would be, in fact, a special case that has stabilized the {120} surfaces, which are structurally different from the {210} facets. The {120} surface has a slightly higher surface energy than the {210} surface (surface energies of 1.68 and 1.65 J/m2, respectively, calculated with force field methods). {120} pyritohedra from Elba, Italy, are growing next to micaceous iron oxides (a type of hematite), which are also peculiar specimens with magnetic properties. Another specificity is that some rare earth elements have been identified in the pyrite sample from Elba, which leads to a hypothesis that geothermal conditions favor "negative" striations (e.g., discernible in Akita prefecture-Japan, Boyacá-Colombia, and Cassandra-Greece). The striation directions become useful to distinguish (hkl) surfaces and to identify twinning as they follow the same patterns on each interpenetrated crystal. The most common twinning is the "iron cross," a penetration twin of two crystals defined by a rotation of 90° along an [001] axis with a coincidence in the iron sub-lattice (e.g., twinning by merohedry) and with a twin center. The sulfur network also plays a fundamental role in stabilizing the (001) interface and in keeping the chemical bulk properties at the boundary, as confirmed by additional ab initio simulations. The grain boundary is a 2D defect in which the (001) twinning is relatively stable as it is common. The calculated formation energy of the rotation twinning is 0.8 J/m2. The rotation twinning is associated with an apparent reflection on (110) planes. The formation energy of the (110) mirror grain boundary is 1.7 J/m2, and the interface at the atomic scale is relatively uniform in agreement with experimental observations. [ABSTRACT FROM AUTHOR]

Pupil diameter, under constant illumination, is known to reflect individuals' internal states, such as surprise about observation and environmental uncertainty. Despite the growing use of pupillometry in cognitive learning studies as an additional measure for examining internal states, few studies have used pupillometry in human motor learning studies. Here, we provide the first detailed characterization of pupil diameter changes in a short-term reach adaptation paradigm. We measured pupil changes in 121 human participants while they adapted to abrupt, gradual, or switching force field conditions. Sudden increases in movement error caused by the introduction/reversal of the force field resulted in strong phasic pupil dilation during movement accompanied by a transient increase in tonic premovement baseline pupil diameter in subsequent trials. In contrast, pupil responses were reduced when the force field was gradually introduced, indicating that large, unexpected errors drove the changes in pupil responses. Interestingly, however, error-induced pupil responses gradually became insensitive after experiencing multiple force field reversals. We also found an association between baseline pupil diameter and incidental knowledge of the gradually introduced perturbation. Finally, in all experiments, we found a strong co-occurrence of larger baseline pupil diameter with slower reaction and movement times after each rest break. Collectively, these results suggest that tonic baseline pupil diameter reflects one's belief about environmental uncertainty, whereas phasic pupil dilation during movement reflects surprise about a sensory outcome (i.e., movement error), and both effects are modulated by novelty. Our results provide a new approach for nonverbally assessing participants' internal states during motor learning. [ABSTRACT FROM AUTHOR]

The longevity of asphalt pavements is a key focus of road engineering, which closely relates to the self-healing ability of bitumen. Our work aims to establish a CGMD model and matched force field for bitumen and break through the limitations of the research scale to further explore the microscopic mechanism of bitumen self-healing. In this study, a CGMD mapping scheme containing 16 kinds of beads is proposed, and the non-bond potential energy function and bond potential energy function are calculated based on all-atom simulation to construct and validate a coarse-grained model for bitumen. On this basis, a micro-crack model with a width of 36.6nm is simulated, and the variation laws of potential energy, density, diffusion coefficient, relative concentration and temperature in the process of bitumen self-healing are analyzed with the cracking rate parameter proposed to characterize the degree of bitumen crack healing. The results show that the computational size of the coarse-grained simulation is much larger than that of the all-atom, which can explain the self-healing mechanism at the molecular level. In the self-healing process, non-bonded interactions dominate the molecular movement, and differences in the decreased rate of diffusion among the components indicate that saturates and aromatics play a major role in self-healing. Meanwhile, the variations in crack rates reveal that healing time is inversely proportional to temperature. The impact of increasing temperature on reducing healing time is most obvious when the temperature approaches the glass transition temperature (300 K). [ABSTRACT FROM AUTHOR]

Despite the massive application of end-point free energy methods in protein–ligand and protein–protein interactions, computational understandings about their performance in relatively simple and prototypical host–guest systems are limited. In this work, we present a comprehensive benchmark calculation with standard end-point free energy techniques in a recent host–guest dataset containing 13 host–guest pairs involving the carboxylated-pillar[6]arene host. We first assess the charge schemes for solutes by comparing the charge-produced electrostatics with many ab initio references, in order to obtain a preliminary albeit detailed view of the charge quality. Then, we focus on four modelling details of end-point free energy calculations, including the docking procedure for the generation of initial condition, the charge scheme for host and guest molecules, the water model used in explicit-solvent sampling, and the end-point methods for free energy estimation. The binding thermodynamics obtained with different modelling schemes are compared with experimental references, and some practical guidelines on maximizing the performance of end-point methods in practical host–guest systems are summarized. Further, we compare our simulation outcome with predictions in the grand challenge and discuss further developments to improve the prediction quality of end-point free energy methods. Overall, unlike the widely acknowledged applicability in protein–ligand binding, the standard end-point calculations cannot produce useful outcomes in host–guest binding and thus are not recommended unless alterations are performed. [ABSTRACT FROM AUTHOR]

The 3D-reference interaction site model (3D-RISM) molecular solvation theory in combination with the Kovalenko–Hirata (KH) closure is extended to seven heterocyclic liquids to understand their liquid states and to test the performance of the theory in solvation free energy (SFE) calculations of solutes in select solvents. The computed solvent site distribution profiles were compared with the all-atom molecular dynamics (MD) simulations, showing comparable performances. The computational results were compared against the structural parameters for liquids, whenever available, as well as against the experimental SFEs. The liquids are found to have local ordered structures held together via weak interactions in both the RISM and MD simulations. The 3D-RISM-KH computed SFEs are in good agreement with the benchmark values for the tetrahydrothiophene-S,S-dioxide, and showed comparatively larger deviations in the case of the SFEs in the tetrahydrofuran continuum. [ABSTRACT FROM AUTHOR]

Phosphorylation plays a key role in plant biology, such as the accumulation of plant cells to form the observed proteome. Statistical analysis found that many phosphorylation sites are located in disordered regions. However, current force fields are mainly trained for structural proteins, which might not have the capacity to perfectly capture the dynamic conformation of the phosphorylated proteins. Therefore, we evaluated the performance of ff03CMAP, a balanced force field between structural and disordered proteins, for the sampling of the phosphorylated proteins. The test results of 11 different phosphorylated systems, including dipeptides, disordered proteins, folded proteins, and their complex, indicate that the ff03CMAP force field can better sample the conformations of phosphorylation sites for disordered proteins and disordered regions than ff03. For the solvent model, the results strongly suggest that the ff03CMAP force field with the TIP4PD water model is the best combination for the conformer sampling. Additional tests of CHARMM36m and FB18 force fields on two phosphorylated systems suggest that the overall performance of ff03CMAP is similar to that of FB18 and better than that of CHARMM36m. These results can help other researchers to choose suitable force field and solvent models to investigate the dynamic properties of phosphorylation proteins. [ABSTRACT FROM AUTHOR]

Individuals with physical limb disabilities are often restricted to perform activities of daily life (ADLs). While efficacy of bilateral training has been demonstrated in improving physical coordination of human limbs, few robots have been developed in simulating people’s ADLs integrated with task-specific force field control. This study sought to develop a bilateral robot for better task rendering of general ADLs (gADLs), where gADL-consistent workspace is achieved by setting linear motors in series, and haptic rendering of multiple bimanual tasks (coupled, uncoupled and semi-coupled) is enabled by regulating force fields between robotic handles. Experiments were conducted with human users, and our results present a viable method of a single robotic system in simulating multiple physically bimanual tasks. In future, the proposed robotic system is expected to be serving as a coordination training device, and its clinical efficacy will be also investigated.

It has been increasingly common to investigate dynamic and thermodynamic properties of green solvents at atomistic scales with molecular simulation. In this work, we present a detailed evaluation of the widely used fixed-charge regime, i.e., the combination of scaled RESP charges and GAFF derivatives. The benchmark set contains three ionic liquids formed by cations 1-butyl-3-methylimidazolium and 1-hexyl-3-methylimidazolium and anions bis(trifluoromethylsulfonyl)imide and PF6. For the charge scaling issue, two physical properties including the mass density and the solvation free energies of external agents in ionic liquids are selected as the criteria. Large-scale fast-growth solvation free energy simulations are performed to obtain the solvation thermodynamics, and the results are further combined with hydration data to form a water-ionic-liquids transfer dataset, which considers the partition of solutes between water and ionic liquids. It is observed that the density-derived charge scaling factor is always smaller than that derived from solvation/partition thermodynamics, which supports the use of a slightly larger scaling factor to obtain a balanced description of solute-solvent and solvent-solvent interactions. For the bonded-terms assessment, we refit the transferable GAFF2 derivatives with generalized force-matching in a molecule- and component-specific manner. The results suggest that the bond-stretching and angle-bending terms in GAFF derivatives are often problematic, while the torsional potential shows satisfactory reproduction of ab initio results. Finally, combining the extensive computational perspectives accumulated in our series works, general guidelines for molecular modelling of ionic liquids with fixed-charge force fields are summarized.

Molecular docking is one of the most popular computational tools for the hit discovery step in drug design. However, there is ample room for improvement of docking's ability to identify correct binding modes and discriminate active from decoy compounds. Molecular dynamics (MD) simulations of protein–ligand docking structures have been shown to be effective in improving docking results. Here, we present CHARMM‐GUI high‐throughput simulator (HTS) that prepares MD simulation systems and inputs for multiple protein–ligand complex structures in a high‐throughput manner. HTS supports commonly used MD programs (NAMD, GROMACS, AMBER, OpenMM, GENESIS, Desmond, LAMMPS, and Tinker) along with various force field combinations for protein and ligand, including CHARMM36m, Amber (ff19SB/ff14SB), OPLS‐AA/M, CGenFF, GAFF2, and OpenFF. Validation tests using Miller and the directory of useful decoys‐enhanced (DUD‐E) datasets demonstrate that short MD simulations using HTS‐generated systems and simple ligand RMSD calculations consistently outperform docking results. Specifically, MD simulations can better identify correct ligand‐binding modes among top 10 binding poses as compared to docking scores. In addition, MD simulations can better discriminate active from decoy compounds in the DUD‐E dataset than docking scores for both soluble and membrane proteins. We expect that HTS can be a useful tool to facilitate the hit discovery process in drug design by improving docking results. [ABSTRACT FROM AUTHOR]

Infrared (IR) spectroscopy is a valuable tool to obtain information about protein secondary structure. The far-infrared (FIR) spectrum is characterized by a complex combination of different molecular contributions which, for small molecules, may be interpreted with the help of quantum-mechanical (QM) calculations. Unfortunately, the high computational cost of QM calculations makes them inapplicable to larger molecules, such as proteins and peptides. In this work, we present a theoretical study on the secondary structure, molecular properties, and vibrational spectra of different peptides, using both a classical and a QM approach. Our results show that the amide I main peak value, and related quantities, such as dipole strength (DS) and transition dipole moment (TDM), depends on protein secondary structure; in particular, from QM calculations arises that α -rich molecular systems present lower intensities than β -rich ones. Furthermore, it is possible to decouple and identify the intensity of the different contributions of the inter- and intra-molecular motions which characterize the FIR spectrum, starting from the results obtained with QM calculations. [ABSTRACT FROM AUTHOR]

Metal–organic frameworks (MOFs) are a highly versatile group of porous materials suitable for a broad range of applications, which often crucially depend on the MOFs' heat transport properties. Nevertheless, detailed relationships between the chemical structure of MOFs and their thermal conductivities are still largely missing. To lay the foundations for developing such relationships, we performed non-equilibrium molecular dynamics simulations to analyze heat transport in a selected set of materials. In particular, we focus on the impact of organic linkers, the inorganic nodes and the interfaces between them. To obtain reliable data, great care was taken to generate and thoroughly benchmark system-specific force fields building on ab-initio-based reference data. To systematically separate the different factors arising from the complex structures of MOF, we also studied a series of suitably designed model systems. Notably, besides the expected trend that longer linkers lead to a reduction in thermal conductivity due to an increase in porosity, they also cause an increase in the interface resistance between the different building blocks of the MOFs. This is relevant insofar as the interface resistance dominates the total thermal resistance of the MOF. Employing suitably designed model systems, it can be shown that this dominance of the interface resistance is not the consequence of the specific, potentially weak, chemical interactions between nodes and linkers. Rather, it is inherent to the framework structures of the MOFs. These findings improve our understanding of heat transport in MOFs and will help in tailoring the thermal conductivities of MOFs for specific applications. [ABSTRACT FROM AUTHOR]

In this work we have derived the parameters of an AMOEBA-like polarizable forcefield for electrolytes based on tetramethoxy and tetraethoxy-glyoxal acetals, and propylene carbonate. The resulting forcefield has been validated using both ab-initio data and the experimental properties of the fluids. Using molecular dynamics simulations, we have investigated the structural features and the solvation properties of both the neat liquids and of the corresponding 1 M LiTFSI electrolytes at the molecular level. We present a detailed analysis of the Li ion solvation shells, of their structure and highlight the different behavior of the solvents in terms of their molecular structure and coordinating features., (© 2024 The Authors. ChemistryOpen published by Wiley-VCH GmbH.)

Despite the successes of antibodies as therapeutic binding proteins, they still face production and design challenges. Alternative binding scaffolds of smaller size have been developed to overcome these issues. A subset of these alternative scaffolds recognizes target molecules through mutations to a set of surface resides, which does not alter their backbone structures. While the computational design of antibodies for target epitopes has been explored in depth, the same has not been done for alternative scaffolds. The commonly used dock-and-mutate approach for binding proteins, including antibodies, is limited because it uses a constant sequence and structure representation of the scaffold. Docking fixed-backbone scaffolds with a varied group of surface amino acids increases the chances of identifying superior starting poses that can be improved with subsequent mutations. In this work, we have developed MutDock, a novel computational approach that simultaneously docks and mutates fixed backbone scaffolds for binding a target epitope by identifying a minimum number of hydrogen bonds. The approach is broadly divided into two steps. The first step uses pairwise distance alignment of hydrogen bond-forming areas of scaffold residues and compatible epitope atoms. This step considers both native and mutated rotamers of scaffold residues. The second step mutates clashing variable interface residues and thermodynamically unfavorable residues to create additional strong interactions. MutDock was used to dock two scaffolds, namely, Affibodies and DARPins, with ten randomly selected antigens. The energies of the docked poses were minimized and binding energies were compared with docked poses from ZDOCK and HADDOCK. The top MutDock poses consisted of higher and comparable binding energies than the top ZDOCK and HADDOCK poses, respectively. This work contributes to the discovery of novel binders based on smaller-sized, fixed-backbone protein scaffolds.

This research focuses on obtaining the behavior of chemical compounds with respect to their molecular weight and optimization energy based on the variation in properties in organic carbon links. Here, behavioral analysis of compounds is used in the application of a metal organic framework to denote the high-grade compounds. The grade was selected based on the essential measure of optimization energy and molecular weight, and in turn, depicts the stability of material. Computation of the optimization energy and molecular weight of chemical compounds was performed with Avogadro software. Several force fields can be considered to compute optimized energy. Exclusively, three force fields, namely, the Universal Force Field (UFF), the General Amber Force Field (GAFF), and the Ghemical force field (Ghemical) were selected from Avogadro as these were more relevant to compounds considered in this research. The various chemical compounds examined in this work are Aluminum (Al), Boron (Br), Calcium (Ca), Chlorine (Cl), Indium (In), Potassium (K), Scandium (Sc), Silicon (Si), and Tungsten (W). Hence, molecular modeling of different compounds incorporated with three different force fields was evaluated in this work. In this study, we found that the In structure has more energy reduction, of 22.673 kJ mol−1 in UFF, when compared with the other two force fields. Thus, In has higher potential with more stability.

The applicability of the three steps systematic parametrization procedure (3SSPP) to develop a force field for primary amines was evaluated in the present work. Previous simulations of primary amines show that current force fields (FF) can underestimate some experimental values under room conditions. Therefore, we propose a new set of parameters, for an united atom (UA) model, that can be used for short and long amines which predict correctly thermodynamic and dynamical properties. Following the 3SSPP methodology, the partial charges are chosen to match the experimental dielectric constant whereas the Lennard-Jones (LJ) parameters, ε and σ, are fitted to reproduce the surface tension at the vapor-liquid interface and the liquid density, respectively. Simulations were initially conducted for the propylamine molecule by introducing three different types of carbon atoms, C_α and C_β, with electric charges, and C_n, without charge. Then, modifying the charges of the carbons and using the transferable LJ parameters, the new set of constants for long amines were found. The results show good agreement for the experimental dielectric constant and mass density with a percentage error less than 1% surface tension the error is up to 4% ethylamine, the new charges were obtained from a fitting function calculated from the long amines results. For these molecules, the values of the dielectric constant and the surface tension present errors of the order of 10% with the experimental data. Miscibility of the amines was also tested with the new parameters and the results show reasonable agreement with experiments.

Thermal conductivities of polybutadiene crosslinked with sulfur as a function of the heat flux autocorrelation function by using an equilibrium molecular dynamic (EMD) simulation were investigated. The Green–Kubo method was used to calculate thermal conductivities. All simulations were performed by applying the LAMMPS software (version 3 Mar 2020) package. The united-atom force field (OPLS-UA) from the Moltemplate software (version 2.20.3) was applied in the simulations. The influence of uniform and random distributions of sulfur in polybutadiene on the final value of thermal conductivities was studied by polymeric model structures with similar and variable degrees of crosslinking. The results showed that for identical degrees of crosslinking, the distribution of crosslinkers in the polymeric model structures significantly influenced the final value of thermal conductivity. Moreover, the influence of the crosslinking degree on the final value of thermal conductivity was studied by considering polymeric model structures with different degrees of crosslinking. The results demonstrate that by having a random distribution of sulfur, the thermal conductivity will be enhanced. However, by increasing the degree of crosslinking to the higher percentage in random crosslinked model structures, the value of thermal conductivity drops significantly due to possible higher crystallization of the model structures, which decrease the degree of freedom for phonon contributions.

A new force field for 1-propanol, in the united and all atom models, has been obtained by combining two different empirical methodologies. The first was developed by scaling atom charges and Lennard-Jones parameters to fit the dielectric constant, surface tension, and density; this methodology is named three steps systematic parameterization procedure (3SSPP), as reported by Pérez de la Luz et al. (J Chem Theory Comput 14:5949–5958, 2018). The second methodology consists of moving these parameters and together with the bond distance to obtain the liquid-vapor phase diagram of the CO2 molecule as discussed by Harris and Yung (J Phys Chem 99:12021–12024, 1995). The last methodology is used to obtain the self-diffusion coefficient, which was not consider in the 3SSPP. The 3SSPP/bond methodology is the 3SSPP plus the bond distance scaling. With this new methodology, the experimental density, dielectric constant, surface tension, and self-diffusion coefficient at ambient temperature could be achieved. Furthermore, we show the temperature dependence of the aforementioned properties. The static structure factors are in accordance with the experimental spectrum. Solubility is increased to the experimental value for the united atom (UA) model after applying this methodology and for all atom (AA) scheme, the experimental solubility value is maintained. [ABSTRACT FROM AUTHOR]

Molecular mechanics force field calculations have historically shown significant limitations in modeling the energetic and conformational interconversions of highly substituted furanose rings. This is primarily due to the gauche effect that is not easily captured using pairwise energy potentials. In this study, we present a refinement to the set of torsional parameters in the General Amber Force Field (gaff) used to calculate the potential energy of mono, di-, and gem-fluorinated nucleosides. The parameters were optimized to reproduce the pseudorotation phase angle and relative energies of a diverse set of mono- and difluoro substituted furanose ring systems using quantum mechanics umbrella sampling techniques available in the IpolQ engine in the Amber suite of programs. The parameters were developed to be internally consistent with the gaff force field and the TIP3P water model. The new set of angle and dihedral parameters and partial charges were validated by comparing the calculated phase angle probability to those obtained from experimental nuclear magnetic resonance experiments. [ABSTRACT FROM AUTHOR]

We provide tailor-made GAFF2-type interaction potentials for modeling ammonium and amide ions in ammonia. Based on harmonic approximation of intra-molecular bond stretching and bending, our force fields nicely reproduce the vibrational modes of NH4+ and NH2−, respectively. Moreover, quantum calculations of pair-wise NH4+/NH2−–NH3 interactions were used for inter-molecular force field parameterization, while (NH3)n, [(NH4)(NH3)n]+, and [(NH2)(NH3)n]− complexes with n > 2, respectively, were reserved for benchmarking in terms of both structure and formation energy. Despite the limited reliability of molecular mechanics models for describing dimer complexes (n = 1), we find that GAFF2 reasonably reproduces [(NH4)(NH3)n]+ species for n = 2–4. For the assessment of [(NH2)(NH3)n]− complexes with n = 2–4, we however suggest the introduction of specific van der Waals parameters for amide-ammonia interactions. The application of the (extended) GAFF2 models is demonstrated for the study of ammonium and amide solvation in liquid ammonia at 240 K and 1 atm, respectively. On this basis, we suggest the applicability of our model for both gas phase and liquid states of ammonia. [ABSTRACT FROM AUTHOR]

Hexagonal boron nitride (hBN), a promising 2D nanomaterial, has potential applications in desalination and osmotic energy harvesting. In all these applications, surface roughness significantly impacts fluid flow in nanomaterial, but its precise effect remains unclear. This creates a knowledge gap in understanding how surface roughness influences water flow at the water-hBN interface, which hinders the development of accurate molecular dynamics (MD) simulations. Here, we address this gap by employing density functional theory (DFT) to calculate atomic charges on rough hBN surfaces. These charges are incorporated into MD simulations, revealing a strong influence on the water-hBN interface. This combined approach accurately predicts experimental water slip length. We further quantify the water flow behavior on hBN using established force fields. Incorporating surface roughness into the model yields results in close agreement with the experimental slip length of ∼ 1 nm for water using FF-2 force fields, validating the simulation approach. Our findings highlight the importance of incorporating realistic surface roughness and force field models in MD simulations of water-nanomaterial interfaces. This work underscores the critical role of accurate 2D material models for understanding fluid flow in nanofluidic applications. [Display omitted] • Surface roughness accurately predicts water slip length (∼ 1 nm) on hBN. • Surface roughness increases friction and reduces slip length on hBN. • Potential to tailor slip length by manipulating roughness. • Close agreement with the experimental slip length of ∼ 1 nm using FF-2 force fields. • Study enhances understanding of nanoscale friction at water-hBN interfaces. [ABSTRACT FROM AUTHOR]

We re-investigate the image charge model of Iori and Corni (Iori and Corni, J. Comput. Chem. 2008, 29, 1656). We find that a simple symmetrization of their model allows to obtain quantitatively correct results for the electrostatic interaction of a water molecule with a metallic surface. This symmetrization reduces the magnitude of the electrostatic interaction to less than 10% of the total interaction energy. © 2017 Wiley Periodicals, Inc.